Decomposition methods in stochastic programming

@article{Ruszczynski1997DecompositionMI,
  title={Decomposition methods in stochastic programming},
  author={Andrzej Ruszczynski},
  journal={Math. Program.},
  year={1997},
  volume={79},
  pages={333-353}
}
Stochastic programming problems have very large dimension and characteristic structures which are tractable by decomposition. We review basic ideas of cutting plane methods, augmented Lagrangian and splitting methods, and stochastic decomposition methods for convex polyhedral multi-stage stochastic programming problems. @ 1997 The Mathematical Programming Society, Inc. Published by Elsevier Science B.V. 

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References

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Showing 1-10 of 26 references

A parallel implementation of the nested decomposition method for multistage stochastic linear programs

  • C. J. Donohue, D. E Holmes, O. G. Svintsitski
  • Mathematical Programming
  • 1996

Scenario analysis via bundle decomposition

  • A. Madansky
  • Annals of Operations Research
  • 1995

The integer L - shaped method for stochastic integer programs with complete recourse

  • EV. Louveaux
  • Operations Research Letters
  • 1995

Ruszczyfiski, On optimal allocation of undivisibles under uncertainty, Operations Research, to appear

  • V. I. Norkin, A. YuM. Ermoliev
  • Mathematical Programming
  • 1994

Splitting algorithms for the sum of two nonlinear operators

  • EL. Lions, B. Mercier
  • SlAM Journal on Numerical Analysis
  • 1993

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